Dynamic Load Transfer Strategy of Campus Distribution Network Based on Genetic Algorithm

摘要

At present, the campus distribution network (CDN) has become an important part of the urban distribution network, but the transformation and upgrading of the distribution network cannot match the growth of the school electricity load. Therefore, there are many problems such as unbalanced load between transformers, excessive peak-and- valley difference within transformers and unbalanced three-phase power existing in the universities. This thesis firstly analyzes the energy usage rules in order to summarize the common problems and causes of CDN. And then this paper proposes a dynamic load transfer strategy based on outgoing side optimization and flexible connection. Finally, taking the actual distribution network of a university in Beijing as an example, an optimization model is established and solved by genetic algorithm. The results of the example analysis indicate that the method can balance the load of each transformer while reducing the transformer loss.